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Staff Applied Machine Learning Engineer - Intelligent Data, Signals & Systems at Block - ApplyBlast

Staff Applied Machine Learning Engineer - Intelligent Data, Signals & Systems

Block

4 months ago

3.6 on Glassdoor

Bay Area

Onsite

Full Time

Senior

0 applicants

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About this role

This Staff Applied Machine Learning Engineer role focuses on building and operating production ML systems that generate trusted signals for recommendations, ranking, risk decisioning, and customer intelligence across Block's diverse portfolio. The incumbent will design composable signal interfaces, oversee full-lifecycle ML workflows, and partner with product teams to ensure fairness, reliability, and measurable business impact.

Responsibilities

Build and operate production ML systems for recommendation and ranking
Design production data and signal contracts for downstream consumers
Own end-to-end ranking, retrieval, and next-best-action systems
Evaluate customer impact including trust, fairness, and long-term engagement
Partner across teams to translate goals into measurable ML system designs

Skills

Qualifications

BS in Computer ScienceMS in Machine LearningProfessional Engineer License

About Block

block.xyz

Headquarters

Oakland, California, United States

Company Size

10001+ employees

Founded

2009

View Profile

Block, Inc. builds technology to increase access to the global economy by connecting businesses and consumers across commerce, payments, and financial services. Its ecosystem includes Square (merchant point‑of‑sale, payments, hardware and business tools), Cash App (peer‑to‑peer payments, banking, investing and crypto), Afterpay (buy‑now‑pay‑later), TIDAL (music streaming), Bitkey (blockchain/security products) and Proto (R&D and product incubation). Block offers payments processing, merchant services, lending, payroll, subscriptions, developer APIs and integrated hardware aimed at simplifying commerce for small businesses and individuals. The company emphasizes developer-friendly tools and consumer apps to expand financial inclusion globally.